Life, Knowledge and Natural Selection ―

How life (scientifically) designs its future

William P. Hall President Kororoit Institute Proponents and Supporters Assoc., Inc. - http://kororoit.org william-hall@bigpond.com http://www.orgs-evolution-knowledge.net

Science Technology Future Symposium Philosophy of Science – Future by Design

August 23-24, 2014

Access my research papers from Google Citations

Attribution CC BY

Note: underlined text links to the Web

Three main topics for today

Unified theory of knowledge and life (life does science to live) – Karl Popper (1972) evolutionary epistemology – what makes K reliable?

“General theory of evolution” – error elimination and the inevitable growth of K Three ontological domains (worlds) – physical, mental, encoded knowledge

– Epistemic cut – Howard Pattee (1995 ) concept from biophysics – Autopoiesis - Maturana and Varela (1980) - reliable K makes systems living

Evolution and revolutions in cognition & knowledge Thomas Kuhn (1970) – Major cognitive revolutions (= step changes) from the beginning of memory

and life Origin of memory and cognition in dynamic structure Genetic memory Cultural memory

– Add technology Explicit/Tangible memory & communication (i.e., writing & printing) Virtual memory, cognition & communication at light speed

Moore’s Law – compresses time and space through exponential growth – 5 million years of human history concatenates many technological/cognitive

revolutions – Will we reach a post-human singularity in our life times?

Extract from “Application Holy Wars or a New Reformation – A fugue on the theory of knowledge”

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My background for this presentation

Microscopy, protozoology & marine biology as a curious child

Physics (1957-59)

Hands on work with digital computers (1958)

Zoology (BS San Diego State Univ, 1964)

Evolutionary biology (1960) PhD Harvard (1973) studying lizard genetics, cytogenetics, systematics, and speciation

History and philosophy of science while at U Melb. (1977-79)

Computer literacy education and tech communication (1982)

Banking systems analysis & documentation (1988-89)

Documentation and knowledge management systems analysis and design for Tenix Defence on $7 BN ANZAC Ship Project (1990-2007)

Exploring the co-evolution of knowledge and life at all levels of organization (2001 )

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Biologically-based theory of knowledge

and life

Scientific knowledge is tested solutions to problems (Popper)

All living things “do” science to stay alive

PART ONE

Popper 1959 – “The Logic of Scientific Discovery”; 1963 – Conjectures and Refutions:

– There is no such thing as induction – We can’t prove if we know the truth – Deductive falsification is deterministic – Make bold hypotheses and try to falsify them –

what is left is better than what has been falsified – Demarcation between science and pseudoscience based on

falsifiability (stringent testing to eliminate errors) – More clued in to physical and biological sciences than most philosophers

Popper (1972 – “Objective Knowledge – An Evolutionary Approach”) – Knowledge as solutions to problems – All knowledge is constructed – Falsification also not reliable: claims can be protected against falsification

by infinite regress of auxiliary hypotheses – “Tetradic schema” to eliminate errors and build knowledge – “Three worlds” ontology

Many contemporary philosophers misunderstand Objective Knowledge – especially radical constructivists (e.g., Constructivist Foundations)

– “Objective knowledge” = knowledge inertly codified into/onto a physical object (DNA, print on paper, pits on a CD, domains on a magnetic surface)

What makes knowledge reliable? Karl Popper’s biologically-based epistemology

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Karl Popper’s first big idea: "tetradic schema“ / "evolutionary theory of knowledge" / "general theory of evolution"

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Pn a real-world problem faced by a living entity

TS a tentative solution/theory. Tentative solutions are varied through serial/parallel iteration

EE a test or process of error elimination

Pn+1 changed problem as faced by an entity incorporating a surviving solution

The whole process is iterated

TSs may be embodied as dynamic “structure” in the individual entity, or

TSs may be expressed in words as hypotheses, subject to objective criticism; or as genetic codes in DNA, subject to natural selection

Explicit expression and criticism of theories lets them die in our stead

Through cyclic iteration of creation and criticism, sources of errors are found and eliminated

Surviving solutions become more reliable, i.e., approach reality

Surviving TSs are the source of all knowledge!

Popper (1972), pp. 241-244

Popper's second big idea from Objective Knowledge: “three worlds” ontology

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Energy flow Thermodynamics

Physics Chemistry

Biochemistry

Cybernetic self-regulation

Control information Cognition

Consciousness “Tacit” knowledge

Genetic heredity Recorded thought Computer memory Logical artifacts

“Explicit” knowledge

Select/Encode/Reproduce

Recall/Decode/Instruct

World 1

Existence/Reality

World 2 World of mental or psychological states and processes, subjective experiences, memory of history Organismic/personal/situational/ subjective/tacit knowledge in world 2 emerges from interactions with world 1

World 3 The world of “objective” knowledge Produced / evaluated by world 2 processes

living knowledge

codified knowledge

dynamics & life

Howard Pattee’s “Epistemic cut” concept clarifies relationships between biophysical reality and Popper’s three worlds

Popper did not physically justify his ontological proposal

Howard Pattee (1995) “Artificial life needs a real epistemology” – An “epistemic cut” (a.k.a. “Heisenberg cut”) in both physical and philosophical

senses refers to strict ontological separation between: Knowledge of reality from reality itself, e.g., description from construction, simulation

from realization, mind from brain. Selective evolution began with a description-construction cut.... The highly evolved cognitive epistemology of physics requires an epistemic cut between reversible dynamic laws and the irreversible process of measuring [or describing]….

– No evidence Pattee or Popper ever cited the other

– See Pattee (2012) Laws, Language and Life. Biosemiotics vol. 7 (key chapter)

One epistemic cut separates blind physics of world 1 from cybernetic “control information” (Corning 2001) for self-regulation, cognition, and living memory in world 2

A second epistemic cut separates the self-regulating dynamics of living entities from the knowledge objectively encoded in books, computer memories and DNAs and RNAs

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Varela et al. (1974) define life as autopoiesis Reliable knowledge makes systems living

Six criteria are necessary and sufficient for autopoiesis – Bounded

System components self-identifiably demarcated from environment

– Complex Separate and functionally different subsystems exist within boundary

– Mechanistic System dynamics driven by self-sustainably regulated flows of energy

from high to low potential driving dissipative “metabolic” processes

– Self-defining System structure and demarcation intrinsically produced Control information/survival knowledge embodied in instantaneous

structure

– Self-producing (= “auto” + “poiesis”) System intrinsically produces own components

– Autonomous self-produced components are necessary and sufficient to produce the

system.

Autopoiesis is a good definition for life

Autopoiesis (Maturana & Varela 1980; see also Wikipedia) – Reflexively self-regulating, self-sustaining, self-(re)producing dynamic entity

– Continuation of autopoiesis depends on the dynamic structure of the state in the previous instant producing an autopoietic structure in the next instant through iterated cycles ()

– Selective survival builds knowledge into the system one problem solution at a time (Popper 1972, 1994)

By surviving a perturbation, the living entity has solved a problem of life

Structural knowledge demonstrated by self-producing cellular automata

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Doing “science” makes a system living

Constraints and boundaries, regulations determine what is physically allowable

Energy (exergy)

Component recruitment

Materials

Observation

s

Entropy/Waste

Products

Departures

Actions

ProcessesProcesses

"universal" laws governing component interactions determine physical capabilities

The entity's imperatives and goals

The entity's history and present circumstances

HIGHER LEVEL SYSTEM / ENVIRONMENT

SUBSYSTEMS / COMPONENTS

Constraints and boundaries, regulations determine what is physically allowable

Energy (exergy)

Component recruitment

Materials

Observation

s

Entropy/Waste

Products

Departures

Actions

ProcessesProcesses

"universal" laws governing component interactions determine physical capabilities

The entity's imperatives and goals

The entity's history and present circumstances

HIGHER LEVEL SYSTEM / ENVIRONMENT

SUBSYSTEMS / COMPONENTS

Gliders – cycle in 4 steps

Gosper’s Glider Gun cycles in 14 steps

Rule: Live cell with 2 or 3 live neighbours lives Dead cell with 3 live neighbours lives All other live cells die

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Some OODA definitions after Col. John Boyd’s OODA Loop process

Generic process for any complex adaptive entity – Observation assembles data about the world (including the entity's

own prior effects and those of its competitors on that world). Data is given context relating to interactions with the world.

– Orientation processes information from those observations into semantically linked knowledge to form a world view comprised of recent observations memories of prior experience (which may be explicit, implicit or even

tacit) genetic heritage (i.e., "natural talent") cultural traditions (i.e., paradigms) sense making (i.e., inferring meaning) analysis (destruction) of the existing world view synthesis (creation) of a revised world view including possibilities for

action. This generates intelligence (in a military sense). – Decision selects amongst possible actions generated by the

orientation, action(s) to try. Choice is governed and informed by wisdom based on experience gained from previous OODA cycles

– Action puts tests decisions against the world. The loop begins to repeat as the entity observes the results of its action.

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Popper's General Theory of Evolution + John Boyd’s (1996) OODA Loop process

O = Observation of reality; O = Making sense and orienting to observations with solutions to be tested; D = Selection of a solution or making a “decision”

A = Application of decision or "Action" on reality

The real world is a filter that penalizes/eliminates entities that act on mistaken decisions or errors (i.e., Darwinian selection operates) Conscious self-criticism eliminates bad ideas If errors remain, the environment penalizes or eliminates entities

acting on the errors – Reality trumps belief

TS1 TS2 • • •

TSm

Pn Pn+1 A On EE EE

Self criticism

Environmental criticism /filter

Reality trumps belief

Slide 13

Information transformations in the living entity through time

World 1

Living system Cell

Multicellular organism Social organisation

State

Perturbations

Observations (data)

Classification

Meaning

An "attractor basin"

Related information

Memory of history

Semantic processing to form knowledge

Predict, propose

Intelligence

World 2

Hall, W.P., Else, S., Martin, C., Philp, W. 2011. Time-based frameworks for valuing knowledge: maintaining strategic knowledge. Kororoit Institute Working Papers No. 1: 1-28. (OASIS Seminar Presentation, Department of Information Systems, University of Melbourne, 27 July 2007)

Slide 14

Processing Paradigm (may include W3)

Another view

Decision

Medium/ Environment Autopoietic system

World State 1

Perturbation Transduction

Observation Memory Classification

Evaluation

Synthesis

Assemble Response

Internal changes

Effect action

Effect

Time

World State 2

Iterate Observed internal changes

World 1 World 2

World 3

Evolution and revolutions in living

systems

Evolutionary vs revolutionary

capabilities for growing knowledge

Evolution vs revolutions

Thomas Kuhn (1970) – Structure of Scientific Revolutions (= chaotic & discontinuous changes in non-linear systems)

– Normal Science = incremental evolutionary change within an established world view/cognitive structure

– Scientific Revolution = discontinuous change resulting from emergence of a new/disruptive cognitive structure

Concepts apply more broadly than scientific theory – Technology – normal technological development disrupted by

new technologies doing same things in new ways

– Biology – slow incremental change producing better adaptations to local peaks in the adaptive landscape, may be punctuated by “grade shifts” creating new landscapes opening new realms for adaptive radiations

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Time-line for the most fundmental revolutions in knowledge storage, processing power and bandwidth

Memory and cognition in dynamic structure of the autopoietic system (W2 only) – 4.5 billion years ago – physics begets life

– Virtuous cyclical dynamics at the molecular level able to maintain homeostatic control in some circumstances

Genetic memory at the molecular level (W2 + W3) - 4 bn years ago – Add RNA & DNA

Multicellular memory (molecular W2 + W3 + cellular W2) – 2-1.5 bn years ago

– Add dynamic structure in cellular neurons neural nets brains

Group cultural memory (molecular W2 + W3 + cellular W2 + organizational W2) – 5 million years ago

– Add tacit then linguistic creation, communication & sharing of knowledge

Codification, storage & transfer of knowledge in and via tangible artefacts, e.g., writing & communication (molecular W2 + W3 + cellular W2 + organizational W2 + W3) – 5 thousand years ago

Virtual memory, communication, cognition at light speed – 50 years ago

Global brain – now! 17

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Knowledge-based revolutions in material technology cause grade shifts in the ecological nature of the human species

Accelerating change in our material technologies: – > 5 million years ago - Tool Making: sticks and stone tools plus

fire (~ 1 mya) extend human reach, diet and digestion

– ~ 11 thousand years ago - Agricultural Revolution: Ropes and digging implements control and manage non–human organic metabolism

– ~ 560 years ago Printing enables Reformation & Scientific Revolution

– ~ 2.5 ca - Industrial Revolution: extends/replaces human and animal muscle power with inorganic mechanical power

– ~ 50 years ago - Microelectronics Revolution: extends human cognitive capabilities with computers

– ~ 5 years ago - Cyborg Revolution: convergence of human and machine cognition with smartphones (today) and neural prosthetics (tomorrow)

PART TWO

Evolution and revolutions in living

systems

Evolutionary vs revolutionary

capabilities for growing knowledge

Evolution vs revolutions

Science = processes for growing reliable knowledge Thomas Kuhn (1970) – Structure of Scientific

Revolutions (= discontinuous & chaotic changes in non-linear systems)

– Normal Science = incremental evolutionary change within an established world view/cognitive structure

– Scientific Revolution = discontinuous change resulting from emergence of a new/disruptive cognitive structure

Concepts apply more broadly than scientific theory – Biology

Incremental change providing better adaptations to local peaks in the adaptive landscape

May be punctuated by “grade shifts” providing access to new landscapes opening new realms for adaptive radiations

– Technology – normal technological development disrupted by new technologies doing old + new things in new ways

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Timeline for the most fundmental revolutions in biological knowledge storage, processing power and bandwidth

Memory and cognition emerged in dynamic structure of the autopoietic system (W2 only) – 4.5 billion years ago – physics begets life

– Virtuous cyclical dynamics at the molecular level able to maintain homeostatic control in some circumstances

Genetic memory at the molecular level (W2 + W3) - 4 bn years ago – Add RNA & DNA

Multicellular memory (molecular W2 + W3 + cellular W2) – 2-1.5 bn years ago

– Add dynamic structure in cellular connections neurons nets brains

Group cultural memory (molecular W2 + W3 + cellular W2 + organizational W2) – 5 million years ago

– Add tacit then linguistic creation, communication & sharing of knowledge

Codification, storage & transfer of knowledge in and via tangible artefacts, e.g., writing & communication (molecular W2 + W3 + cellular W2 + organizational W2 + W3) – 5 thousand years ago

Virtual memory, communication, cognition at light speed – 50 years ago

Global brain – now! 21

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Grade shifting revolutions in human technologies repeatedly reinvent the nature of & bandwidths for individual cognition

Accelerating change in extending human cognition – (> 5 mya – Tacit transfer of tool-using/making knowledge adds

cultural inheritance to genetic inheritance) – (~ 2 mya - Emergence of speech speeds direct transfer/

criticism of cultural knowledge among individuals) – ~ 11 kya – Invention of physical counters (11 K), writing and

reading (5 K) to record and transmit knowledge external to human memory (technology to store & transfer culture)

– ~ 5.6 ca - printing and universal literacy transmit knowledge to the masses (cultural use of technology)

– ~ 32 ya - computing tools actively manage corporate data/ knowledge externally to the human brain (32 Y) and personal knowledge (World Wide Web - 18 Y)

– ~ 10 ya- smartphones merge human and technological cognition (human & technological convergence)

– ~ Now: Emergence of human-machine cyborgs (wearable and implanted technology becoming part of the human body)

5 million years of human history

concatenates many cognitive

revolutions

Where we started: socially foraging, tool-using forest apes in East African Garden of Eden > 5 mya

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Adaptive plateaus achieved in the Pliocene as our ancestors became more bipedal and better adapted to open and arid environments (White et al. 2009)

Chimps use probes to collect ants. Probe is inserted almost to full length into earth.

Child watching mother crack otherwise inedible palm nuts using stone hammer & anvil.

(click pictures below to view videos)

Knowledge-based autopoietic groups as higher-order evolutionary entities

Accumulated knowledge determines system’s structural adaptations to ensure survival and (re)production

Hierarchically nested systems are possible – Cells Organisms Social organizations Communities

A group is defined to be autopoietic if it exhibits all the criteria – Bounded (groups geographically and socially separated with culturally regulated

and limited mixing) – Complex (groups formed of several to many individuals playing various different

roles in group) – Mechanistic (energetically/economically driven interactions of group individuals

determine group functions) – Self-referential (group identity and boundaries determined by culturally

transmitted knowledge) – Self-producing (group retains its continuity beyond the lifetimes of single

individuals through individual reproduction and recruitment combined with indoctrination in and transmission of accumulated cultural knowledge from one generation to the next)

– Autonomous (the group manages its own survival and continuity through knowledge-based interactions of its individual members) 25

Advances in group/organization cognition combined with technology enable other grade shifting revolutions

Genetic memory is adaptive

Cultural memory is additive as well as adaptive !

Accelerating change in extending group cognition – > 5 million years ago – social hunting/defence cooperative foraging & hunting autopoietic groups

– ~ 2.0 mya - linguistically coordinated activities to share group knowledge (mime, dancing, singing, story-telling, myth, ritual)

– ~ 200 thousand years ago – mnemonics/songlines apply ritual & method of loci to landscapes to build & retain cultural memories

– ~ 12 kya – mnemonic guilds & monumental architectures enable husbandry, settlement, farming & economic specialization

– ~ 7 kya – tokens & writing enable bureaucratic cities & states

– ~ 600 years ago – communications, coordination & rise of chartered companies

– ~ 100 ya – instant communication & rise of transnationals

– ~ Now – emergence of global brain & global cognition

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Scientifically constructing formal knowledge to control the world (Hall & Nousala 2010; Vines & Hall 2011)

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Exponential growth and Moore’s Law

The incredible shrinking of

time and space

PART THREE

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Knowledge-based revolutions in material technology cause grade shifts in the ecological nature of the human species

Accelerating change in human material technologies: – > 5 million years ago - Tool Making: stick and stone tools plus

fire (~ 1 mya) extend human reach, diet and digestion

– ~ 11 thousand years ago - Agricultural Revolution: Ropes and digging implements control and manage non–human organic metabolism

– ~ 560 years ago Printing enables Reformation & Scientific Revolution

– ~ 250 years ago - Industrial Revolution: extends/replaces human /animal muscle power with inorganic mechanical power

– ~ 50 years ago - Microelectronics Revolution: extends human cognitive capabilities with computers

– ~ 5 years ago - Cyborg Revolution: convergence of human and machine cognition with smartphones (today) and neural prosthetics (tomorrow)

30

Microelectronics Revolution Large scale integration and Moore’s Law

Moore's Law as applied to the evolution of microprocessors. Recent studies show the rate of increase is actually hyper-exponential. Magnetic storage density doubles even faster, as does total processing power. Chips are 4004 (2300 transistors, 1971), 8008 (3500 transistors - 1972), and Dual-Core Intel® Itanium® Processor (1.3 BN transistors - 2006)

Hyperexponential growth in computing technology

Beyond flat IC’s – 3D IC’s Heat

management

– Biomolecular (e.g., DNA) Speed

Transduction

Interface

– Quantum Heat

management

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Ray Kurzweil 2013

The Microelectronics Revolution and the increasing externalization and convergence of individual and social cognition

――― Externalizing cognition ―――

~ 150 Y mechanical and electro/mechanical technologies for corporate/scientific number crunching & data processing

~ 60 Y birth of electronic digital processing

~ 43 Y invention of integrated circuit microprocessors and automatic fabrication Moore’s Law & the still continuing hyperexponential growth of processing power

Extending and replacing more and more human cognition

~ 35 Y automated processing, storage, distribution and retrieval of personal and corporate knowledge. (Wordstar 1979)

~ 22 Y networking knowledge with the World Wide Web (Tim Berners-Lee 1992) ――― Universal access to the world knowledge base ―――

~ 20 Y Mosaic Netscape Navigator 1994

~ 16 Y free open-source browsers Mozilla Firefox 1998

~ 14 Y one billion web pages indexed, more than two billion by end of 2000 Last decade provides instant web search, access & retrieval of virtually the entire

scientific & technical literature via Google Scholar/research library subscriptions

Majority of all English language book titles scanned, indexed, and available (if out of copyright), with smaller fractions non-English books processed.

――― Networking brains directly – towards a global brain/mind? ――― 32

Emergence of the networked

post-human cyborg still driven by

natural selection

Interconnecting minds and cognitive processes via the cloud, “social computing” and convergent technology

Technological convergence – mobile phone becomes a cognitive prosthesis – Email: ARPANET (1971), TCP/IP (1982), SMS text (2002),Gmail (2005)

– Internet browsing & Search: MOSAIC/Netscape (1994),Google (!997)

– Internet telephony: Voice over IP (1994), Skype (2003)

– Media: iTunes (2000), Amazon Kindle (2007), Google Play (2008)

– Still and video imaging: Picassa/iPhoto (2002); YouTube (2005);

– Cloud storage: Napster (1999), BitTorrent (2001), Amazon S3 (2006), DropBox (2008)

– Business/Office tools: Google Docs/Drive (2007)

– Geospatial: Google Earth/Maps 2005; Panoramio (geolocated photos converging with Google Earth/Google Maps – 2005)

– Social: chat rooms (1980); Groups/Listservers (1992), LinkedIn (2003), Facebook (2004), Twitter (2006)

– Knowledge construction/sharing/broadcasting: Wikis (1994), Wikipedia (2002), Blogs/Wordpress (2003)

Human-computer interfacing – Head-mounted displays (1960’s)

– Google Project Glass (2013)

– Networked SmartWatches (2014)

Implanted/embodied human-machine interfaces – Cochlear implants/Bionic Ears

– Retinal implants/Bionic Eyes

– Direct brain reading and stimulation 34

Sensory integration: Count on Moore’s Law to drive the price down

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Direct stimulation of the cochlea (Graeme Clark Foundation, How the cochlear implant (bionic ear) functions.)

Direct stimulation of the retina (Bionic Eye. DOE Artificial Retina Project)

Brain simulation and emulation Blue Brain Project / Human Brain Project

Human Connectome Project – US NIH funded 2010-2015

– Map of neural connections in the brain

– Broadly, a connectome includes mapping of all neural connections in an organism's nervous system

Simulation & emulation – Modelling of synapses & neurons

– Neurons on chips (Moore’s Law)

– EU Blue Brain/Human Brain Projects Single cell: 2005

Neocortical column: 2008 – 10,000 cells

Mesocircuit: 2011 – 100 columns

Rodent brain: ~2014 – 100 mesocircuits

Human brain: ~2023 – 1000 x rodent brains

36

Will knowledge growth end in a singularity, spike or inflected S curve?

37

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THE END

Papers elaborating the ideas can be found on http://www.orgs-evolution-knowledge.net. For working drafts and extracts see https://www.dropbox.com/sh/odx80z06k1bsbb4/AADrCRlSdqv8ivBPKPov8oHwa